Systems and methods for validating repeating data

ABSTRACT

A computing system for validating repeating data is described. The computing system includes at least one computing device including at least one processor communicatively coupled to a database. The at least one processor is programmed to receive a first instance of data, the first instance of data including first repeating data elements, and store, in the database, the first repeating data elements. The at least one processor is also programmed to receive a second instance of data, the second instance of data including second repeating data elements, determine the second instance of data includes the second repeating data elements, and compare the second repeating data elements to the first repeating data elements. The at least one processor is further programmed to determine the second repeating data elements are inconsistent with the first repeating data elements and transmit a signal associated with the second repeating data elements.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 16/838,921, filed Apr. 2, 2020, which isincorporated herein by reference in its entirety.

BACKGROUND

The field of the invention relates generally to validating repeatingdata, and more specifically, systems and methods for monitoringrepeating data, such as installment payments, and triggering events thatmay cause alerts to be transmitted and/or declines to be initiated.

In today's world there are many forms of repeating data that need to bevalidated. Many users associated with repeating data are only given thechoices of verifying the repeating data manually, or not verifying it atall. Repeating data may include, for example, repeated payments, such asfor a gym membership, and installment payments for goods and/orservices. It is a hassle for users to remember to check repeating data.If users do remember to check repeating data it is also inconvenient tomanually check the repeating data and verify that the repeating data iscorrect. Thus, systems and methods are needed for validating repeatingdata and prompting a user when the repeating data is not valid or isotherwise inconsistent with what it should be.

Consumers today often have various payment options to pay merchants forgoods and/or services. One such option is to set up installmentpayments, wherein a consumer pays a fixed amount at a fixed frequencyfor a fixed period of time in order to pay the merchant. The fixedperiod of time during which payments are made may last over severalmonths, or even years. Over time, some customers, who are used to beingbilled for the installments, may stop monitoring the installmentpayments to ensure the correct amount is being charged at the properfrequency. This may lead to overbilling, double-billing, and/or billingafter installment payments should have stopped.

Therefore, there is a need for systems and methods that can alertcustomers to inconsistent payment requests and/or block unauthorizedinstallment payments, and more specifically, systems and methods formonitoring installment payments and/or installment payment requests andtriggering events based on installment payment (IP) data.

BRIEF DESCRIPTION

In one aspect a computing system for validating repeating data isdescribed. The computing system includes at least one computing deviceincluding at least one processor communicatively coupled to a database.The at least one processor is programmed to receive a first instance ofdata, the first instance of data including first repeating dataelements, and store, in the database, the first repeating data elements.The at least one processor is also programmed to receive a secondinstance of data, the second instance of data including second repeatingdata elements, determine the second instance of data includes the secondrepeating data elements, and compare the second repeating data elementsto the first repeating data elements. The at least one processor isfurther programmed to determine the second repeating data elements areinconsistent with the first repeating data elements and transmit asignal associated with the second repeating data elements.

In another aspect, a method for monitoring installment payments andtriggering events based on installment payment (IP) data is provided.The method includes receiving, at a processor, a first transactionrequest, the first transaction request including first IP request dataand determining, by the processor, that the first transaction request isassociated with the first installment payment by determining that thefirst transaction request includes the first IP request data. The methodalso includes storing, in a database, the first IP request data as firstIP data, receiving, at the processor, a second transaction request, thesecond transaction request including second IP request data, anddetermining, by the processor, that the second transaction requestincludes the second IP request data. The method further includescomparing, by the processor, the second IP request data to the first IPdata, determining, by the processor, the second IP request data isinconsistent with the first IP data, and transmitting, from theprocessor, a signal associated with the second transaction request.

In yet another aspect, at least one non-transitory computer-readablestorage media having computer-executable instructions embodied thereonis described. When the computer-executable instructions are executed byat least one processor, the computer-executable instructions cause theIP computing device to receive a first transaction request, the firsttransaction request including first IP request data and determine thatthe first transaction request is associated with the first installmentpayment by determining that the first transaction request includes thefirst IP request data. The computer-executable instructions also causethe IP computing device to store, in a database, the first IP requestdata as first IP data, receive a second transaction request, the secondtransaction request including second IP request data, and determine thatthe second transaction request includes the second IP request data. Thecomputer-executable instructions further cause the IP computing deviceto compare the second IP request data to the first IP data, determinethe second IP request data is inconsistent with the first IP data, andtransmit a signal associated with the second transaction request.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1-8 show example embodiments of the systems and methods describedherein.

FIG. 1 is a schematic diagram illustrating an example installmentpayment (IP) computing system for monitoring installment payments andtriggering events based on IP data.

FIG. 2 is an example data flow diagram illustrating the monitoring ofinstallment payment (IP) data, implemented using the IP computing systemshown in FIG. 1 .

FIG. 3 is an example data flow diagram illustrating notifying a user ofa merchant-requested inconsistent installment payment and blocking theassociated installment payment request, implemented using the IPcomputing system shown in FIG. 1 .

FIG. 4 is an example data flow diagram illustrating notifying a user ofa merchant-requested consistent installment payment, implemented usingthe IP computing system shown in FIG. 1 .

FIG. 5 illustrates an example configuration of a user computing deviceshown in FIG. 1 , in accordance with one embodiment of the presentdisclosure.

FIG. 6 illustrates an example configuration of server components formonitoring installment payments using the IP computing system shown inFIG. 1 .

FIG. 7 is a flow chart of an example process for monitoring installmentpayments and triggering events via the IP computing system shown in FIG.1 .

FIG. 8 is a diagram of components of one or more example computingdevices that may be used in the IP computing system shown in FIG. 1 .

DETAILED DESCRIPTION

The following detailed description illustrates embodiments of thedisclosure by way of example and not by way of limitation. Thedescription enables one skilled in the art to make and use thedisclosure. It also describes several embodiments, adaptations,variations, alternatives, and uses of the disclosure, including what ispresently believed to be the best mode of carrying out the disclosure.

The systems and methods described herein relate to validating repeatingdata, and more specifically to monitoring and validating periodicallyrepeating data. Repeating data may include, for example, data thatrepeats on a periodic basis at a defined frequency. The frequency atwhich the repeating data is repeated may be defined at a first instanceand detected by a computing system for validating repeating data. Otherdata elements of the repeating data may also be detected by thecomputing system at the first instance, such as the total period of timeover which the data will repeat in addition to the frequency at whichthe data will repeat. Further, the computing system may be configured todetect future instances of the repeating data, and compare those futureinstances of the repeating data to previous instances of the repeatingdata, including the first instance of repeating data. Thus, thecomputing system for validating repeating data may be configured todetermine when instances of repeating data are inconsistent withprevious instances of the repeating data. In other words, the computingsystem may be configured to detect when a current instance of repeatingdata is inconsistent with previous instances of the repeating data bydetermining, for example, the current instance of repeating data isinconsistent with the defined frequency at which data will repeat and/oris inconsistent with the defined total period of time over which thedata will repeat.

For example, a computing system for validating repeating data, includingat least one computing device with at least one processorcommunicatively coupled to a database may be provided. The at least oneprocessor may be programmed to receive a first instance of data, thefirst instance of data including first repeating data elements includinga length of time over which instances of repeating data will bereceived, a frequency at which instances of repeating data will bereceived, and other information that is expected to be received infuture instances of data. The first instance of data may be used todefine a repeating data plan. The repeating data plan may then be usedby the at least one processor when the at least one processor receivesfuture instances of data, such as a second instance of data or thirdinstance of data. The at least one processor may also be programmed todetermine the first instance of data is associated with a firstrepeating data plan by determining that the first instance of dataincludes the first repeating data elements, store, in a database, thefirst repeating data elements, receive a second instance of data, thesecond instance of data including second repeating data elements, anddetermine the second instance of data includes the second repeating dataelements and is associated with a first repeating data plan. The atleast one processor may further be programmed to compare the secondrepeating data elements to the first repeating data elements, determinethe second repeating data elements are inconsistent with the firstrepeating data elements, and transmit a signal associated with thesecond repeating data elements. The data elements compared by the atleast one processor may include, for example, the length of time overwhich instances of repeating data will be received with a date of thesecond instance of data and/or the frequency at which instances ofrepeating data will be received with the date of the first instance ofdata and the date of the second instance of data.

In some embodiments, the at least one processor may also be configuredto determine a user preference before transmitting a signal associatedwith the second repeating data elements. In these embodiments, the userpreference may be, for example, an alert transmitted to a user computingdevice or to transmit a signal rejecting the second instance of data. Inembodiments where the user preference is for an alert to be transmittedto a user computing device, the processor may further be configured toreceive a signal from the user computing device to reject the secondinstance of data.

In other embodiments, the processor may be further configured to, uponreceipt of the second instance of repeating data, including secondrepeating data elements, determine if the second repeating data elementshave already been stored in the database and yet further configured tocompare instances of repeating data to other associated instances ofrepeating data stored in the database.

The computing system for validating repeating data may be, for example,an installment payment (IP) computing system configured to monitor andvalidate installment payment data, as is described below.

An IP computing system configured to monitor installment payments andtrigger events based on installment payment (IP) request data isdescribed herein. In the example embodiment, the IP computing system isconfigured to provide an IP service as described further herein. The IPcomputing system includes at least one IP computing device, at least oneissuer computing device, at least one merchant computing device, atleast one installment payment (IP) database, at least one alert control(AC) database, and/or at least one user computing device.

The IP service enables a user to easily track installment payments overa period of time. For example, a user may purchase a good or servicefrom a merchant, wherein payment for the good and/or service is agreedto be split and spread out over a period of time as installment payments(e.g., for a $600 purchase, paying $100 (or some higher amount toaccount for interest payments) a month over 6 months). After the usercompletes a first installment payment, the IP system generates, fromtransaction data associated with the completed installment payment, aninstallment definition that identifies an installment plan establishedbetween the merchant and the user (e.g., an amount, frequency, andlength of installment payments, such as $100, once a month, for 6months). The IP system tracks subsequent or future installment paymentsand/or future installment payment requests to determine whether thesubsequent installment payments/requests are in compliance with thedefined installment plan. Upon determining an installment paymentrequested by a merchant is not in compliance with the establishedinstallment plan, the IP computing device is configured to block therequested payment and/or notify the user of the inconsistent requestand/or payment, depending on a user preference. Accordingly, a user cantake comfort in knowing the IP computing system is monitoring theirinstallment plan, including an amount charged for installment payments,the length of time over which installment payments will be made, and afrequency with which installment payments will be made, and can identifyaberrant installment payment requests before the user makes anunnecessary or incorrect payment.

The IP computing device may be associated with or integral to a paymentnetwork (e.g., an interchange network for processing the installmentpayments), such that the IP computing device may access incoming IPrequests and outgoing completed installation payments. Alternatively,the IP computing device may not be part of the payment network but iscommunicatively coupled to one or more payment processors to receiveincoming IP requests and outgoing completed installation paymentstherefrom. In still other embodiments, the IP computing device isassociated with the issuer computing device, and the IP service isavailable through the issuer. In such embodiments, the IP computingdevice receives incoming IP requests and outgoing completed installationpayments from the issuer computing device.

Further, the IP computing device may be configured to determine when anIP request is included in a larger request, such as a transactionrequest, by processing the data associated with the transaction request.For example, the IP computing device may determine an IP request isincluded in a transaction request upon determining certain data elementsexist in the transaction request that correspond to an IP request. Inthis example, the transaction request may be in the form of anauthorization request and/or response message. The authorizationresponse and/or response message may be formatted as a network message,such as an ISO 8583 network message, such that data elements may bewithin or appended to the network message. The data elementscorresponding to an IP request may include data elements indicating, forexample, the number of installment payments to be made, the frequency atwhich installment payments will be made, the total length of time overwhich installment payments will be made, and the amount requested by amerchant for the installment payments.

In the example embodiment, the IP database and the AC database arecommunicatively coupled to the IP computing device. The IP database andthe AC database are separate from each other, and, in at least someembodiments, the IP and AC databases are in communication with the IPcomputing device over different communication networks in a distributedarchitecture. In some alternative embodiments, the IP database and theAC database may be the same database, but IP data and alert preferences(described further herein) may be stored separately.

The AC database is configured to store data associated with alertpreferences of users. User alert preferences are selected or set byusers, and identify whether and how each user wishes to receive alertsregarding their installment plan and payments thereof. A user may be,for example, a consumer, payor, and/or cardholder associated with one ormore installment payments. A user alert preference may be, for example,that the user wishes to receive an alert when any inconsistent IPrequest is received (or completed), and/or that the user wants anyinconsistent IP request to be declined before a payment associatedtherewith is completed. The data stored by the AC database includes, butis not limited to, an account identifier (e.g., a payment account number(PAN) such as a virtual PAN or tokenized PAN), user contact information,and a user alert preference, indicating a user-preferred response by theIP computing device when the IP computing device determines amerchant-requested installment payment is inconsistent with aninstallment payment plan.

The IP database is configured to store data associated with installmentpayments of users. The IP computing device may be configured todetermine data to be stored in the IP database, such as certain dataelements within or appended to an authorization request and/or responsemessage formatted as a network message, as is described above. The datastored in the IP database includes, but is not limited to, an accountidentifier (e.g., a virtual PAN or tokenized PAN) associated with thepayment account used to make installment payments, an amount charged forinstallment payments, a length of time for installment payments (e.g.,the period of time over which installment payments will be made), and afrequency of installment payments. In the example embodiment, the usercompletes a first transaction with the merchant after receiving a firsttransaction request, the first transaction request including first IPrequest data indicating the merchant's request for the first installmentpayment in the installment plan. The first transaction request isgenerated by the merchant, at a merchant computing device associatedtherewith (e.g., a point-of-sale (POS) device). The user completes thefirst transaction, thereby completing the first installment payment. Thecompleted payment (made by the user) is processed by at least onepayment network and at least one issuer computing device. The firsttransaction request data may include any data related to the firsttransaction request and/or the completed payment associated therewith,such as, for example, a location of the transaction, a time of thetransaction, an amount charged for the transaction, and firstinstallment payment (IP) request data.

The IP computing device is configured to identify first IP request datain the first transaction request, and store the first IP request data asfirst IP data in the IP database. The first IP data may include, forexample, an account identifier, an amount charged for the firstinstallment payment, the length of time for installment payments, andthe frequency of installment payments. In at least some embodiments,this first IP data may be included in an authorization request and/orresponse message (e.g., as data elements within or appended to such amessage which may be formatted as a network message, such as an ISO 8583network message).

At a later time, the merchant computing device will request a secondtransaction, associated with a second installment payment, bytransmitting a second transaction request (e.g., an authorizationrequest) including second IP request data. The merchant computing devicewill transmit the second transaction request to the payment network,which is in communication with the IP computing device. The IP computingdevice will then perform a lookup in the IP database for first IP data(or other associated IP data). The IP computing device will then comparethe second IP request data, from the received second transactionrequest, to the stored first IP data. The comparison may includecomparing, for example, an amount charged for the first installmentpayment with an amount charged for the second installment paymentrequest, a length of time for installment payments with a date of thesecond installment payment request (to make sure the date is within atime frame agreed upon by the user and the merchant), and a frequency ofinstallment payments with the date of the first installment payment andthe date of the second installment payment request (to ensure thepayments are not being made too far apart or too close together). Insome embodiments, a length of time for installment payments may be atotal length of time of installment payments, defined by an end date, ora total number of expected installment payments at the frequency ofinstallment payments.

If the comparison shows inconsistencies between the first IP data andthe second IP request data, the IP computing device is configured totransmit a signal associated with the second transaction request. Beforetransmitting the signal associated with the second transaction request,the IP computing device determines a user preference by performing alookup in the AC database for any user preference (e.g., using theaccount identifier or other data elements common to installment paymentsfor a same installment plan). In some embodiments, the user preferenceis to decline the second transaction request. In these embodiments, theIP computing device is configured to transmit the signal as a declineinstruction message to the issuer computing device associated with theuser's payment account, instructing the issuer to decline the secondtransaction request. Alternatively, the IP computing device may transmitthe signal to the merchant computing device as a decline message, viathe issuer computing device and the payment network, to decline thesecond transaction request. In further embodiments, the user preferenceis to receive an alert associated with the second transaction request.In these embodiments, the IP computing device is configured to transmitthe signal to the user computing device associated with the user,notifying the user of the second transaction request that isinconsistent with the first installment payment. In these embodiments,the user may be presented with, at the user computing device, an optionto then block the second transaction request (e.g., cause the secondinstallment payment request to be declined). Upon a user request toblock the second transaction request, the IP computing device isconfigured to transmit a signal to the merchant computing device, via anissuer computing device and a payment network, to block the secondtransaction.

In further embodiments, the IP computing device may be configured tocompare IP request data associated with one user to stored IP dataassociated with a different user. For example, the IP database may nothave any stored IP data for the IP computing device to compare with theIP request data (e.g. IP computing device receives a third installmentpayment request, but first and second IP data are not stored in the IPdatabase). In these examples, the IP computing device may be configuredto compare the IP request data to similar IP data associated withdifferent users (e.g., from the same merchant, for the same product,etc.) stored in the IP database.

In these further embodiments, a processor or a processing element may betrained using supervised or unsupervised machine learning, and themachine learning program may employ a neural network, which may be aconvolutional neural network, a deep learning neural network, areinforced or reinforcement learning module or program, or a combinedlearning module or program that learns in two or more fields or areas ofinterest. Machine learning may involve identifying and recognizingpatterns in existing data, such as IP data stored in the IP database, inorder to facilitate making predictions for subsequent data, such as IPrequest data. Models may be created based upon example inputs in orderto make valid and reliable predictions for novel inputs.

Additionally or alternatively, the machine learning programs may betrained by inputting sample (e.g., training) data sets or certain datainto the programs, such as IP data stored in the IP database and/orprojected future IP request data. The machine learning programs mayutilize deep learning algorithms that may be primarily focused onpattern recognition, and may be trained after processing multipleexamples. The machine learning programs may include Bayesian programlearning (BPL), voice recognition and synthesis, image or objectrecognition, optical character recognition, and/or natural languageprocessing—either individually or in combination. The machine learningprograms may also include natural language processing, semanticanalysis, automatic reasoning, and/or other types of machine learning,such as deep learning, reinforced learning, or combined learning. In theexemplary embodiment, IP data feeds back into the machine learningprograms in real-time to update its set of parameters.

Supervised and unsupervised machine learning techniques may be used. Insupervised machine learning, a processing element may be provided withexample inputs and their associated outputs, and may seek to discover ageneral rule that maps inputs to outputs, so that when subsequent novelinputs are provided the processing element may, based upon thediscovered rule, accurately predict the correct output. In unsupervisedmachine learning, the processing element may be required to find its ownstructure in unlabeled example inputs. In the exemplary embodiment,machine learning techniques are used to predict IP request data, and tooutput the predictions that are stored in the IP database.

In the exemplary embodiment, a processing element may be trained byproviding it with a large sample of IP data (e.g., regarding installmentpayments completed by different users and/or installment paymentrequests from different merchants). Such information may include, forexample, information associated with amounts (e.g., dollar amounts),frequency, and length of time for completing installment payments.

Based upon these analyses, the processing element may learn how toidentify characteristics and patterns that may then be applied toanalyzing IP data and/or IP request data. For example, the processingelement may learn to predict consistent and/or inconsistent IP requestsfrom certain merchants. Similarly, the processing element may also learnto identify which data elements are more likely than others to beincorrect and/or inconsistent in an IP request (e.g., an amount chargedin an IP request).

In further embodiments, the IP computing device may be configured totransmit the signal associated with the second transaction request onlyif the comparison shows a discrepancy between the received IP requestdata and the stored installment payment data that is larger than acertain threshold. Relatively low discrepancies or differences betweenstored IP data and received IP request data may occur due to factorssuch as interest, currency conversion differences, and the like. Forexample, if the second IP request data differs from the first IP data byless than a dollar, the IP computing device may not transmit any signalassociated with the second transaction request.

As another example, if a transaction request, including an installmentpayment request, is made a day earlier or a day later than expected, theIP computing device may not transmit any signal to the user, because thedifference of a day may not be a big enough difference to warrant anotification (e.g., such a discrepancy may be due to the difference inthe number of days in consecutive months and may not represent an actualerror). If, however, a transaction request is made a week early, such adiscrepancy may exceed a predefined threshold and therefore may causethe IP computing device to transmit the signal associated with thetransaction request.

In some embodiments, different thresholds may be set by the user (e.g.,as part of their user preferences). Thresholds may also be predeterminedby an issuer or payment network, for example. In these embodiments, theuser may be able to adjust the predetermined thresholds to betteraccommodate their preferences.

The IP computing device may also be configured to transmit anotification to the user computing device even when the second IPrequest data does comply with the stored first IP data. Thus, the userwould be notified that the IP system is performing the IP service bymonitoring their installment payments, even though the installmentpayments are being requested and completed correctly (e.g., consistentwith the installment plan).

In some embodiments, a user may request to receive an update on theirinstallment payments (e.g., their progress towards completing theinstallment plan) from the IP computing device. In these embodiments,the IP computing device is configured to transmit installment paymentprogress data to the user computing device, which provides an update onthe user's progress towards completing the installment plan. Forexample, the installment plan progress data many include a number ofinstallment payments completed, a remainder of time for the installmentplan, a number of expected subsequent installment payments yet to bemade, and the like. In one example, the installment payment progressdata may show that installment payments are $100.00 each, installmentpayments will be made for three more months, installment payments aremade once per month, and currently three installment payments have beenmade (e.g., out of six total scheduled installment payments). Thus, theuser will know they have three installment payments left to be made, ata frequency of once per month for the next three months, of $100.00each.

In the example embodiment, the IP computing device is configured to onlystore IP request data in the IP database as IP data if the transactionassociated with the IP request data is completed. For example, if atransaction request, including an IP request, is declined and/orblocked, the IP device may not store the IP request data in the IPdatabase as IP data. This ensures future comparisons of IP request datato IP data will only include comparisons of IP request data to accurateIP data.

At least some of the technical problems addressed by this systeminclude: (a) users/customers not diligently monitoring installmentpayments manually as time passes from an initial installment payment;(b) user desire to have installment payments monitored automatically inorder to save time; (c) incorrect installment payments being charged tocustomers, and not being caught in time to have the requestedinstallment payment declined; and (d) user desire to check a currentstatus and history of installment payments.

A technical effect of the systems and processes described herein isachieved by performing at least one of: (a) receiving, at a processor, afirst transaction request, the first transaction request including firstIP request data; (b) determining, by the processor, that the firsttransaction request is associated with the first installment payment bydetermining that the first transaction request includes the first IPrequest data; (c) storing, in a database, the first IP request data asfirst IP data; (d) receiving, at the processor, a second transactionrequest, the second transaction request including second IP requestdata; (e) determining, by the processor, that the second transactionrequest includes the second IP request data; (f) comparing, by theprocessor, the second IP request data to the first IP data; (g)determining, by the processor, the second IP request data isinconsistent with the first IP data; and (h) transmitting, from theprocessor, a signal associated with the second transaction request.

The technical effects and advantages achieved by this system may includeat least one of: (a) storing installment payment information such as theamount, length or duration, and frequency of installment payments, (b)automatically monitoring installment payments to ensure the correctamount is being charged (e.g., preventing over-charging), (c)automatically monitoring installment payments to ensure the payments arebeing charged at the correct frequency (e.g., preventing double-billing)(d) automatically monitoring installment payments to ensure no paymentsare being billed beyond the correct duration of an installment plan, (e)providing users comfort in knowing their installment payments are beingcharged properly, and (f) saving users time by them not having to checkeach installment payment manually.

In one embodiment, a computer program is provided, and the program isembodied on a computer-readable medium. In an example embodiment, thesystem is executed on a single computer system, without requiring aconnection to a server computer. In a further example embodiment, thesystem is run in a Windows® environment (Windows is a registeredtrademark of Microsoft Corporation, Redmond, Wash.). In yet anotherembodiment, the system is run on a mainframe environment and a UNIX®server environment (UNIX is a registered trademark of X/Open CompanyLimited located in Reading, Berkshire, United Kingdom). In a furtherembodiment, the system is run on an iOS® environment (iOS is aregistered trademark of Apple Inc. located in Cupertino, Calif.). In yeta further embodiment, the system is run on a Mac OS® environment (Mac OSis a registered trademark of Apple Inc. located in Cupertino, Calif.).The application is flexible and designed to run in various differentenvironments without compromising any major functionality. In someembodiments, the system includes multiple components distributed among aplurality of computing devices. One or more components are in the formof computer-executable instructions embodied in a computer-readablemedium. The systems and processes are not limited to the specificembodiments described herein. In addition, components of each system andeach process can be practiced independently and separately from othercomponents and processes described herein. Each component and processcan also be used in combination with other assembly packages andprocesses.

In one embodiment, a computer program is provided, and the program isembodied on a computer-readable medium and utilizes a Structured QueryLanguage (SQL) with a client user interface front-end for administrationand a web interface for standard user input and reports. In anotherembodiment, the system is web enabled and is run on a business entityintranet. In yet another embodiment, the system is fully accessed byindividuals having an authorized access outside the firewall of thebusiness-entity through the Internet. In a further embodiment, thesystem is being run in a Windows® environment (Windows is a registeredtrademark of Microsoft Corporation, Redmond, Wash.). The application isflexible and designed to run in various different environments withoutcompromising any major functionality.

As used herein, an element or step recited in the singular and precededwith the word “a” or “an” should be understood as not excluding pluralelements or steps, unless such exclusion is explicitly recited.Furthermore, references to “example embodiment” or “one embodiment” ofthe present disclosure are not intended to be interpreted as excludingthe existence of additional embodiments that also incorporate therecited features.

FIG. 1 is a schematic diagram illustrating an example installmentpayment (IP) computing system 100 for monitoring installment paymentsand triggering events based on IP data. IP computing system 100 includesat least one IP computing device 102 in communication with at least oneissuer computing device 104 (e.g., via a payment network 106), at leastone merchant computing device 108 (e.g., via payment network 106), andat least one user computing device 110 (e.g., via the Internet). IPcomputing device 102 is further in communication with at least one IPdatabase 112 and at least one alert control (AC) database 114. Databaseserver 116 may be in communication with at least one database, such asIP database 112 and/or alert control (AC) database 114, that may storeand/or process data, such as IP request data, and/or any other datadescribed herein. IP computing device 102 may include a database server116 that facilitates communication between IP computing device 102 IPdatabase 112 and/or AC database 114. In one embodiment, IP database 112and/or AC database 114 may be stored on server 118 and may be accessedby logging on to IP computing device 102 through user computing device110. In an alternative embodiment, IP database 112 and AC database 114are stored remotely from server 118 and may be non-centralized. In someembodiments IP database 112 and AC database 114 may be included in thesame database.

In the example embodiment, merchant computing device 108 is a computingdevice of a merchant at which purchases/installment plans are made.Merchant computing device 108 is configured to generate authorizationrequests associated with transactions, including installment paymentrequests.

In the example embodiment user computing device 110 (e.g., a smartphone,laptop, tablet, etc.) is configured to receive user inputs from a userthereof regarding requested installment payments. User computing device110 is further configured to generate and transmit, to IP computingdevice 102, a signal indicating a user request to block a requestedtransaction.

In the example embodiment issuer computing device 104 is associated withan issuer of a payment account used to set up the installment planand/or make the requested installment payments that are not blocked.

In the example embodiment payment network 106 is an interchange networkwherein when using the interchange network, computers of a merchant bankor a merchant processor will communicate with computers of an issuerbank to determine whether a cardholder's account is in good standing andwhether the purchase/transaction is covered by a cardholder's availablecredit line.

In the example embodiment, a user may make a purchase with a merchantusing a payment account, wherein a purchase price associated with thepurchase will be paid over a series of installment payments, eachinstallment payment made in response to a respective installment paymentrequest from the merchant according to an installment plan establishedbetween the merchant and the user at the time of purchase.

In particular, turning to FIG. 2 , merchant computing device 108 isconfigured to transmit first transaction request data 202 includingfirst installment payment (IP) request data to payment network 106.First transaction request data 202 includes an authorization requestmessage (e.g., an ISO 8582 network message) and includes a plurality ofdata elements such as an account identifier, an amount charged for thefirst installment payment, the length of time for installment payments,and/or the frequency of installment payments. First transaction requestdata 202 is processed by payment network 106. IP computing device 102,which may be in communication with and/or integral to payment network106, also receives first transaction request data 202 including first IPrequest data. IP computing device 102 stores first IP request data, asfirst IP data 204, in IP database 112, thus defining an installment planestablished between the user and the merchant.

At a later period of time, as defined by the installment plan, merchantcomputing device 108 will transmit second transaction request data 206,including second IP request data, to IP computing device 102 via paymentnetwork 106. Upon receipt of second transaction request data 206, IPcomputing device 102 determines second transaction request data 206includes second IP request data 208 defining a second IP request. IPcomputing device 102, using second IP request data 208, then requestsand receives IP data associated with the second IP request data 208 fromIP database 112 (e.g., by performing a lookup operation using an accountidentifier from second transaction request data 206, or another dataelement common to installation payments in a same installment plan). IPcomputing device 102 then receives first IP data 204 from IP database112. In other embodiments, for example, if fourth IP request data isreceived at IP computing device 102 from payment network 106, IPcomputing device 102 will request and receive first IP data, second IPdata, and third IP data from IP database 112. Accordingly, IP computingdevice 102 would then compare the fourth IP request data to the receivedfirst IP data, second IP data, and third IP data.

After receiving first IP data 204 from IP database 112, IP computingdevice 102 is configured to compare first IP data 204 to second IPrequest data 208. The comparison may include, for example, comparing anamount charged for the first installment payment with an amount chargedfor the second installment payment, a length of time for installmentpayments with a date of the second installment payment (to make sure thedate is within a time frame agreed upon by the user and the merchant),and a frequency of installment payments with the date of the firstinstallment payment and the date of the second installment payment (toensure the payments are not being made too far apart or too closetogether).

If the comparison shows inconsistencies between first IP data 204 andsecond installment payment request data 208, IP computing device 102 isconfigured to transmit a signal associated with the second transactionrequest. Before transmitting the signal associated with the secondtransaction request, IP computing device 102 determines a userpreference by performing a lookup in AC database 114 for any userpreference (e.g. using the account identifier or other data elementscommon to installment payments for a same installment plan). In someembodiments, the user preference is to decline the second transactionrequest. In these embodiments, IP computing device 102 is configured totransmit the signal as a decline instruction message to issuer computingdevice 104 associated with the user's payment account, instructing theissuer to decline the second IP request. Alternatively, IP computingdevice 102 may transmit to merchant computing device 108 a declinemessage, via issuer computing device 104 and payment network 106, todecline the second transaction request.

In further embodiments, such as in FIG. 3 , the user preference is toreceive an alert associated with the second transaction request. Inthese embodiments, IP computing device 102 is configured to transmit aninstallment payment alert signal 302 to user computing device 110associated with the user, notifying the user of the second installmentpayment request that is inconsistent with the first installment payment.In these embodiments, the user may be presented with, at user computingdevice 110, an option to then block the second transaction request(e.g., cause the second installment payment request to be declined).Upon a user request to block the second transaction, such as alertresponse 304, IP computing device 102 is configured to transmit a signalto block the second transaction 306 to issuer computing device 104.Issuer computing device 104 then generates a decline message 308 that istransmitted to merchant computing device 108 via payment network 106.

In further embodiments, IP computing device 102 may be configured totransmit the signal associated with the second transaction request onlyif the comparison shows a discrepancy between the received IP requestdata and the stored installment payment data that is larger than acertain threshold. Relatively low discrepancies or differences betweenstored IP data and received IP request data may occur due to factorssuch as interest, currency conversion differences, and the like. Forexample, if the second IP request data differs from the first IP data byless than a dollar, IP computing device 102 may not transmit any signalassociated with the second transaction request.

As another example, if a transaction request, including an IP request,is made a day earlier or a day later than expected, IP computing device102 may not transmit any signal to user computing device 110, becausethe difference of a day may not be a big enough difference to warrant anotification (e.g., such a discrepancy may be due to the difference inthe number of days in consecutive months and may not represent an actualerror). If, however, a transaction request is made a week early, such adiscrepancy may exceed a predefined threshold and therefore may cause IPcomputing device 102 to transmit the signal associated with therequested transaction.

In some embodiments, different thresholds may be set by the user (e.g.,as part of their user preferences). Thresholds may also be predeterminedby an issuer or payment network, for example. In these embodiments, theuser may be able to adjust the predetermined thresholds to betteraccommodate their preferences.

In yet further embodiments IP computing device 102 is configured totransmit a signal even when no discrepancies are found during thecomparison of installment payment data, as is shown in FIG. 4 . In theexample embodiment, IP computing device 102, upon comparing first IPdata with second IP request data, determines there are no discrepanciesbetween first IP data and second IP request data and thus, the second IPrequest is correct. IP computing device 102 then generates a signal 402including instructions to authorize the second transaction request. Theauthorization signal 402 is then transmitted from IP computing device102 to issuer computing device 124, which causes issuer computing device124 to authorize the second transaction request (e.g., by transmittingan authorization response message including an authorization oracceptance of the second transaction request using payment network 106).Upon authorizing the request, issuer computing device 124 transmitsauthorization response 404 to payment network 106. Payment network 106then transmits the authorization response message 404 to merchantcomputing device 108, thereby completing the second transaction,including the second installment payment. It should be readilyunderstood that, in some embodiments, IP computing device 102 may notactively intervene with instructions for issuer computing device 124where the installation payment request is consistent with theinstallment plan, such that the installation payment request proceeds asa regular authorization request to issuer computing device 124 forauthorization.

In the example embodiment, IP computing device 102 is configured togenerate and transmit payment confirmation data 406 to user computingdevice 110, thereby notifying the user that an installment payment wasmade in response to a correct installation payment request. Paymentconfirmation data 406 may include, for example, an amount charged forthe second installment payment, a date the second installment paymentwas made, and a sequence number of the installment payment, indicatingthat this was the second installment payment made for the particularseries of installment payments established in the installment plan.

In some embodiments, a user may request to receive an update on theirinstallment payments (e.g., their progress towards completing theinstallment plan) from IP computing device 102. In these embodiments, IPcomputing device 102 is configured to transmit installment paymentprogress data to the user computing device, which provides an update onthe user's progress towards completing the installment plan. Forexample, the installment plan progress data many include a number ofinstallment payments completed, a remainder of time for the installmentplan, a number of expected subsequent installment payments yet to bemade, and the like. In one example, the installment payment progressdata may show that installment payments are $100.00 each, installmentpayments will be made for three more months, installment payments aremade once per month, and currently three installment payments have beenmade (e.g., out of six total scheduled installment payments). Thus, theuser will know they have three installment payments left to be made, ata frequency of once per month for the next three months, of $100.00each.

FIG. 5 illustrates an example configuration of a user system 502operated by a user 501. In the example embodiment, user system 502 issimilar to user computing device 110 and/or merchant computing device108 (both shown in FIG. 1 ), and may be used by user 501 to interactwith IP computing device 102 (also shown in FIG. 1 ). More specifically,user system 502 may be used to access an IP service provided by IPcomputing device 102, to monitor installment payments and/or installmentpayment requests. In the example embodiment, user system 502 includes aprocessor 505 for executing instructions. In some embodiments,executable instructions are stored in a memory area 510. Processor 505may include one or more processing units, for example, a multi-coreconfiguration. Memory area 510 is any device allowing information suchas executable instructions and/or written works to be stored andretrieved. Memory area 510 may include one or more computer readablemedia.

User system 502 also includes at least one media output component 515for presenting information to user 501. Media output component 515 isany component capable of conveying information to user 501. In someembodiments, media output component 515 includes an output adapter suchas a video adapter and/or an audio adapter. An output adapter isoperatively coupled to processor 505 and operatively couplable to anoutput device such as a display device, a liquid crystal display (LCD),organic light emitting diode (OLED) display, or “electronic ink”display, or an audio output device, a speaker or headphones.

In some embodiments, user system 502 includes an input device 520 forreceiving input from user 501. Input device 520 may include, forexample, a keyboard, a pointing device, a mouse, a stylus, a touchsensitive panel, a touch pad, a touch screen, a gyroscope, anaccelerometer, a position detector, or an audio input device. A singlecomponent such as a touch screen may function as both an output deviceof media output component 515 and input device 520. User system 502 mayalso include a communication interface 525, which is communicativelycouplable to a remote device, such as IP computing device 102.Communication interface 525 may include, for example, a wired orwireless network adapter or a wireless data transceiver for use with amobile phone network, Global System for Mobile communications (GSM), 3G,or other mobile data network or Worldwide Interoperability for MicrowaveAccess (WIMAX).

Stored in memory area 510 are, for example, computer readableinstructions for providing a user interface to user 501 via media outputcomponent 515 and, optionally, receiving and processing input from inputdevice 520. A user interface may include, among other possibilities, aweb browser and client application. Web browsers enable users, such asuser 501, to display and interact with media and other informationtypically embedded on a web page or a website from IP computing system100. A client application allows user 501 to interact with a serverapplication from IP computing system 100, such as the IP service.

FIG. 6 illustrates an example configuration of a server system 601.Server system 601 may include, but is not limited to, IP computingdevice 102 (shown in FIG. 1 ). Server system 601 includes a processor605 for executing instructions. Instructions may be stored in a memoryarea 610, for example. Processor 605 may include one or more processingunits (e.g., in a multi-core configuration) for executing instructions.The instructions may be executed within a variety of different operatingsystems on server system 601, such as UNIX, LINUX, Microsoft Windows®,etc. It should also be appreciated that upon initiation of acomputer-based method, various instructions may be executed duringinitialization. Some operations may be required in order to perform oneor more processes described herein, while other operations may be moregeneral and/or specific to a particular programming language (e.g., C,C#, C++, Java, or other suitable programming languages, etc.).

Processor 605 is operatively coupled to a communication interface 615such that server system 601 is capable of communicating with a remotedevice such as user system 502 (shown in FIG. 5 ) or another serversystem 601. For example, communication interface 615 may receiverequests from user computing device 110 via the Internet, as illustratedin FIG. 1 .

Processor 605 may also be operatively coupled to a storage device 634.Storage device 634 is any computer-operated hardware suitable forstoring and/or retrieving data. In some embodiments, storage device 634is integrated in server system 601. For example, server system 601 mayinclude one or more hard disk drives as storage device 634. In otherembodiments, storage device 634 is external to server system 601 and maybe accessed by a plurality of server systems 601. For example, storagedevice 634 may include multiple storage units such as hard disks orsolid state disks in a redundant array of inexpensive disks (RAID)configuration. Storage device 634 may include a storage area network(SAN) and/or a network attached storage (NAS) system.

In some embodiments, processor 605 is operatively coupled to storagedevice 634 via a storage interface 620. Storage interface 620 is anycomponent capable of providing processor 605 with access to storagedevice 634. Storage interface 620 may include, for example, an AdvancedTechnology Attachment (ATA) adapter, a Serial ATA (SATA) adapter, aSmall Computer System Interface (SCSI) adapter, a RAID controller, a SANadapter, a network adapter, and/or any component providing processor 605with access to storage device 634.

Memory area 610 may include, but are not limited to, random accessmemory (RAM) such as dynamic RAM (DRAM) or static RAM (SRAM), read-onlymemory (ROM), erasable programmable read-only memory (EPROM),electrically erasable programmable read-only memory (EEPROM), andnon-volatile RAM (NVRAM). The above memory types are exemplary only, andare thus not limiting as to the types of memory usable for storage of acomputer program.

FIG. 7 is a flow chart of an example method 700 for monitoringinstallment payments and triggering events via the IP computing systemshown in FIG. 1 . Method 700 includes receiving 702, at a processor(e.g., processor 605), a first transaction request and determining 704,by the processor, that the first transaction request is associated withthe first installment payment by determining that the first transactionrequest includes the first IP request data. Method 700 further includesstoring 706, in a database, the first IP request data as first IP data204, receiving 708, at the processor, a second transaction request, thesecond transaction request including second IP request data and anindication the second IP request data is associated with associated withthe first IP request data, and determining 710, by the processor, thatthe second transaction request includes the second IP request data.Method 700 also includes comparing 712, by the processor, the second IPrequest data to the first IP data 204, determining 714, by theprocessor, the second IP request data is inconsistent with the first IPdata 204, and transmitting 716, from the processor, a signal associatedwith the second transaction request data.

Method 700 may also include, before transmitting the signal associatedwith the second transaction request, determining, by the processor, auser preference. In some embodiments of method 700 the determined userpreference is transmitting an alert to a user computing device andmethod 700 further includes receiving, at the processor, a signal fromthe user computing device to block the second transaction request.

In some embodiments of method 700 the determined user preference istransmitting a signal to an issuer computing device to block the secondtransaction request.

In some embodiments of method 700 the data the processor is configuredto compare includes an amount charged for the first installment paymentrequest with an amount requested for the second IP request, a length oftime for installment payments with a date of the second IP request, anda frequency of installment payments with the date of the first IPrequest and the date of the second IP request.

In certain embodiments method 700 includes comparing, by the processor,IP request data to other associated IP request data stored in the memorydevice.

In some embodiments method 700 includes determining, by the processor,the second IP request data is associated with the first IP request data.

FIG. 8 is a diagram of components of one or more example computingdevices that may be used in the IP computing system shown in FIG. 1 . Insome embodiments, computing device 810 is used to implement installmentpayment (IP) computing device 102 (shown in FIG. 1 ). The computercomponents may be used to monitor installment payments and transmitsignals to other computing devices, such as user computing device 110(shown in FIG. 1 ). Operator 802 (such as a user operating IP computingdevice 102) may access computing device 810 in order to servicecomputing device 810. In some embodiments, database 820 is similar to IPdatabase 112 and/or AC database 114 (both shown in FIG. 1 ). Database820 may be coupled with several separate components within computingdevice 810, which perform specific tasks. In the example embodiment,database 820 includes transaction data 822 and user preference data 824.

Computing device 810 includes database 820, as well as storage devices830, for storing data within database 820, such as storing transactiondata 822 and user preference data 824. Computing device 810 furtherincludes communications component 840 for receiving 702 (shown in FIG. 7) first transaction request data 202, receiving 708 second transactionrequest data 204, receiving, in some embodiments, from user computingdevice 110 a signal to block a transaction, and transmitting 716 asignal associated with the second transaction request data 206.

Computing device 810 further includes analytics component 850 fordetermining 704 (shown in FIG. 7 ) the first transaction requestincludes first installment payment data, determining 710 the secondtransaction request includes second installment payment data, comparing712 second IP request data to first IP data, and determining 714 thesecond IP request data is inconsistent with the first IP data.

Having described aspects of the disclosure in detail, it will beapparent that modifications and variations are possible withoutdeparting from the scope of aspects of the disclosure as defined in theappended claims. As various changes could be made in the aboveconstructions, products, and methods without departing from the scope ofaspects of the disclosure, it is intended that all matter contained inthe above description and shown in the accompanying drawings shall beinterpreted as illustrative and not in a limiting sense.

While the disclosure has been described in terms of various specificembodiments, those skilled in the art will recognize that the disclosurecan be practiced with modification within the spirit and scope of theclaims.

As used herein, the term “non-transitory computer-readable media” isintended to be representative of any tangible computer-based deviceimplemented in any method or technology for short-term and long-termstorage of information, such as, computer-readable instructions,computer-executable instructions, data structures, program modules andsub-modules, or other data in any device. Therefore, the methodsdescribed herein may be encoded as executable instructions embodied in atangible, non-transitory, computer readable medium, including, withoutlimitation, a storage device and/or a memory device. Such instructions,when executed by a processor, cause the processor to perform at least aportion of the methods described herein. Moreover, as used herein, theterm “non-transitory computer-readable media” includes all tangible,computer-readable media, including, without limitation, non-transitorycomputer storage devices, including, without limitation, volatile andnonvolatile media, and removable and non-removable media such as afirmware, physical and virtual storage, CD-ROMs, DVDs, and any otherdigital source such as a network or the Internet, as well as yet to bedeveloped digital means, with the sole exception being a transitory,propagating signal.

As will be appreciated based on the foregoing specification, theabove-described embodiments of the disclosure may be implemented usingcomputer programming or engineering techniques including computersoftware, firmware, hardware or any combination or subset thereof,wherein the technical effect is a flexible and fast system for variousaspects of monitoring repeating data. Any such resulting program, havingcomputer-readable code means, may be embodied or provided within one ormore computer-readable media, thereby making a computer program product,i.e., an article of manufacture, according to the discussed embodimentsof the disclosure. The article of manufacture containing the computercode may be made and/or used by executing the code directly from onemedium, by copying the code from one medium to another medium, or bytransmitting the code over a network.

In addition, although various elements of the transportation controller(TC) computing device are described herein as including generalprocessing and memory devices, it should be understood that the IPcomputing device is a specialized computer configured to perform thesteps described herein for monitoring repeating data, such asinstallment payments, and triggering events that may cause alerts to betransmitted and/or declines to be initiated.

This written description uses examples to disclose the embodiments,including the best mode, and also to enable any person skilled in theart to practice the embodiments, including making and using any devicesor systems and performing any incorporated methods. The patentable scopeof the disclosure is defined by the claims, and may include otherexamples that occur to those skilled in the art. Such other examples areintended to be within the scope of the claims if they have structuralelements that do not differ from the literal language of the claims, orif they include equivalent structural elements with insubstantiallocational differences from the literal language of the claims.

1-20. (canceled)
 21. A computing system comprising at least oneprocessor in communication with at least one memory, wherein the atleast one processor is configured to: receive a first instance of dataassociated with a user account, the first instance of data includingfirst repeating data elements defining a first repeating data plan;receive a second instance of data associated with the user account, thesecond instance of data including second repeating data elements;compare the second repeating data elements to the first repeating dataelements, the second repeating data elements relating to the firstrepeating data elements; identify an inconsistency between the secondrepeating data elements and the first repeating data elements; determinethat the inconsistency satisfies a threshold stored in the at least onememory and associated with the first repeating data plan; and inresponse to the inconsistency satisfying the threshold, transmit anotification to a user computing device associated with the user accountto notify a user associated with the user account of the inconsistency.22. The computing system of claim 21, wherein the at least one processoris further configured to: receive user preference data from the usercomputing device, the user preference data including the threshold; andstore the threshold in the at least one memory.
 23. The computing systemof claim 21, wherein the at least one processor is further configured toidentify the inconsistency between the second repeating data elementsand the first repeating data elements based at least in part on anoutput from a machine learning model.
 24. The computing system of claim21, wherein the at least one processor is further configured to storethe threshold in the at least one memory as defined by an issuer. 25.The computing system of claim 21, wherein the at least one processor isfurther configured to transmit progress data associated with the firstrepeating data plan to the user computing device, wherein the progressdata comprises at least one of a number of payments completed for thefirst repeating data plan, a remainder of time for the first repeatingdata plan, or a number of expected subsequent payments for the firstrepeating data plan.
 26. The computing system of claim 25, wherein theat least one processor is further configured to transmit the progressdata in response to a request from the user computing device.
 27. Thecomputing system of claim 21, wherein the at least one processor isfurther configured to: receive, from the user computing device, aselection of a notification preference of a plurality of notificationpreferences presented at the user computing device; and store, in the atleast one memory, the notification preference as being associated withthe user account.
 28. The computing system of claim 27, wherein the atleast one processor is further configured to: determine, based upon thenotification preference stored in the at least one memory, to transmitthe notification to the user computing device; receive, from the usercomputing device, a signal generated in response to user selection of aselectable control at the user computing device associated with blockinga transaction associated with the second repeating data elements; andcause the transaction to be blocked in response to receiving the signal.29. At least one non-transitory computer-readable storage medium withinstructions stored thereon that, in response to execution by at leastone processor, cause the at least one processor to: receive a firstinstance of data associated with a user account, the first instance ofdata including first repeating data elements defining a first repeatingdata plan; receive a second instance of data associated with the useraccount, the second instance of data including second repeating dataelements; compare the second repeating data elements to the firstrepeating data elements, the second repeating data elements relating tothe first repeating data elements; identify an inconsistency between thesecond repeating data elements and the first repeating data elements;determine that the inconsistency satisfies a threshold stored in the atleast one non-transitory computer-readable storage medium and associatedwith the first repeating data plan; and in response to the inconsistencysatisfying the threshold, transmit a notification to a user computingdevice associated with the user account to notify a user associated withthe user account of the inconsistency.
 30. The at least onenon-transitory computer-readable storage medium of claim 29, wherein theinstructions further cause the at least one processor to: receive userpreference data from the user computing device, the user preference dataincluding the threshold; and store the threshold in the at least onenon-transitory computer-readable storage medium.
 31. The at least onenon-transitory computer-readable storage medium of claim 29, wherein theinstructions further cause the at least one processor to identify theinconsistency between the second repeating data elements and the firstrepeating data elements based at least in part on an output from amachine learning model.
 32. The at least one non-transitorycomputer-readable storage medium of claim 29, wherein the instructionsfurther cause the at least one processor to store the threshold in theat least one non-transitory computer-readable storage medium as definedby an issuer.
 33. The at least one non-transitory computer-readablestorage medium of claim 29, wherein the instructions further cause theat least one processor to transmit progress data associated with thefirst repeating data plan to the user computing device, wherein theprogress data comprises at least one of a number of payments completedfor the first repeating data plan, a remainder of time for the firstrepeating data plan, or a number of expected subsequent payments for thefirst repeating data plan.
 34. The at least one non-transitorycomputer-readable storage medium of claim 33, wherein the instructionsfurther cause the at least one processor to transmit the progress datain response to a request from the user computing device.
 35. The atleast one non-transitory computer-readable storage medium of claim 29,wherein the instructions further cause the at least one processor to:receive, from the user computing device, a selection of a notificationpreference of a plurality of notification preferences presented at theuser computing device; and store, in the at least one non-transitorycomputer-readable storage medium, the notification preference as beingassociated with the user account.
 36. The at least one non-transitorycomputer-readable storage medium of claim 35, wherein the instructionsfurther cause the at least one processor to: determine, based upon thenotification preference stored in the at least one non-transitorycomputer-readable storage medium, to transmit the notification to theuser computing device; receive, from the user computing device, a signalgenerated in response to user selection of a selectable control at theuser computing device associated with blocking a transaction associatedwith the second repeating data elements; and cause the transaction to beblocked in response to receiving the signal.
 37. A method for analyzingrepeating data elements implemented by at least one processor incommunication with at least one memory, the method comprising: receivinga first instance of data associated with a user account, the firstinstance of data including first repeating data elements defining afirst repeating data plan; receiving a second instance of dataassociated with the user account, the second instance of data includingsecond repeating data elements; comparing the second repeating dataelements to the first repeating data elements, the second repeating dataelements relating to the first repeating data elements; identifying aninconsistency between the second repeating data elements and the firstrepeating data elements; determining that the inconsistency satisfies athreshold stored in the at least one memory and associated with thefirst repeating data plan; and in response to the inconsistencysatisfying the threshold, transmitting a notification to a usercomputing device associated with the user account to notify a userassociated with the user account of the inconsistency.
 38. The method ofclaim 37, further comprising: receiving user preference data from theuser computing device, the user preference data including the threshold;and storing the threshold in the at least one memory.
 39. The method ofclaim 37, further comprising transmitting progress data associated withthe first repeating data plan to the user computing device, wherein theprogress data comprises at least one of a number of payments completedfor the first repeating data plan, a remainder of time for the firstrepeating data plan, or a number of expected subsequent payments for thefirst repeating data plan.
 40. The method of claim 37, furthercomprising: receiving, from the user computing device, a selection of anotification preference of a plurality of notification preferencespresented at the user computing device; storing the notificationpreference as being associated with the user account in the at least onememory; determining, based upon the notification preference stored inthe at least one memory, to transmit the notification to the usercomputing device; receiving, from the user computing device, a signalgenerated in response to user selection of a selectable control at theuser computing device associated with blocking a transaction associatedwith the second repeating data elements; and causing the transaction tobe blocked in response to receiving the signal.